Unsupervised Clustering of Olfactory Phenotypes

Abstract

Background Current clinical classifications of olfactory function are based primarily upon a percentage of correct answers in olfactory identification testing. This simple classification provides little insight into etiologies of olfactory loss, associated comorbidities, or impact on the quality of life (QOL). Methods Community-based subjects underwent olfactory psychophysical testing using Sniffin Sticks to measure threshold (T), discrimination (D), and identification (I). The cognitive screening was performed using Mini-Mental Status Examination (MMSE). Unsupervised clustering was performed based upon T, D, I, and MMSE. Post hoc differences in demographics, comorbidities, and QOL measures were assessed. Results Clustering of 219 subjects, mean age 51 years (range 20-93 years) resulted in 4 unique clusters. Cluster 1 was the largest and predominantly younger normosmics. Cluster 2 had the worst olfaction with impairment in nearly all aspects of olfaction and decreased MMSE scores. This cluster had higher rates of smoking, heart disease, and cancer and had the worst olfactory-specific QOL. Cluster 3 had normal MMSE with relative preservation of D and I, but severely impaired T. This cluster had higher rates of smoking and heart disease with moderately impaired QOL. Cluster 4 was notable for the worst MMSE scores, but general preservation of D and I with moderate loss of T. This cluster had higher rates of Black subjects, diabetes, and viral/traumatic olfactory loss. Conclusion Unsupervised clustering based upon detailed olfactory testing and cognitive testing results in clinical phenotypes with unique risk factors and QOL impacts. These clusters may provide additional information regarding etiologies and subsequent therapies to treat olfactory loss.

Visual and bibliometric analysis of chronic rhinosinusitis and nasal polyps

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Visual and bibliometric analysis of Chronic Rhinosinusitis and Nasal Polyps

“…plasminogen activator, and oral CRTH2 antagonist [36][37][38] . On the other hand, Prof. Schlosser Rodney J focused more on olfaction and the surgical treatment of CRS [39][40][41] .…”

Finding Professional Engagement and Connection Through Scholarly Activity

“…2 On a broader level, olfactory testing and cognitive testing utilized for unsupervised clustering was shown by Schlosser et al to provide clinical phenotypes to identify patients with unique risk factors for heart disease, cancer, and diabetes. 3 Similarly, increased awareness of social determinants of health and high-risk exposures for chronic rhinosinusitis are valuable tools for clinicians to be aware of to help with comprehensive treatment and risk assessment for patients. Salman et al demonstrated that age, race, and employment status were significant predictors of high-acuity emergency room visits for patients with sinusitis, and Gill et al found that tobacco exposure increased the adjusted risk of revision sinus surgery, particularly in those with concurrent asthma diagnosis.…”

“…2 On a broader level, olfactory testing and cognitive testing utilized for unsupervised clustering was shown by Schlosser et al to provide clinical phenotypes to identify patients with unique risk factors for heart disease, cancer, and diabetes. 3…”